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Data-Architect PDF

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  • Questions: 257 Q&A's With Detailed Explanation
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  • Exam Name: Salesforce Certified Data Architect (SP25)
  • Last Update: 18-Jun-2025
  • Questions and Answers: 257
  • Single Choice: 172 Q&A's
  • Multiple Choice: 85 Q&A's

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Data-Architect Questions and Answers

Question # 1

Which API should a data architect use if exporting 1million records from Salesforce?

A.

Bulk API

B.

REST API

C.

Streaming API

D.

SOAP API

Question # 2

What 2 data management policies does the data classification feature allow customers to classify in salesforce? Choose 2 answers:

A.

Reference data policy.

B.

Data governance policy.

C.

Data sensitivity level

D.

Compliance categorization policy.

Question # 3

Universal Containers has implemented Salesforce for its operations. In order for customers to be created in their MDM solution, the customer record needs to have the following attributes:

1. First Name

2. Last Name

3. Email

Which option should the data architect recommend to mandate this when customers are created in Salesforce?

A.

Configure Page Layout marking attributes as required fields.

B.

Create validation rules to check If the required attributes are entered.

C.

Mark Fields for the attributes as required under Setup.

D.

Build validation in Integration with MDM to check required attributes.

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Salesforce Data-Architect Exam Dumps FAQs

A Salesforce Data Architect designs, implements, and manages the data architecture for Salesforce deployments. They ensure data is organized, optimized, secure, and scalable to meet the business needs. Responsibilities include:

  • Designing data models that efficiently store and manage Salesforce data.
  • Defining data standards and governance practices for data quality and consistency.
  • Implementing data security measures to protect sensitive information.
  • Integrating Salesforce with external data sources and systems.
  • Automating data processes and workflows for efficiency.
  • Monitoring and optimizing data performance within the Salesforce platform.
  • Strong understanding of data modeling principles and relational databases.
  • Expertise in the Salesforce platform, including its data objects, fields, and relationships.
  • Experience with data integration tools and technologies (e.g., ETL/ELT tools).
  • Proficiency in data governance and data quality best practices.
  • Analytical and problem-solving skills to identify and address data challenges.
  • Excellent communication and collaboration skills to work with stakeholders.

Salesforce Data Architects can progress to senior roles with broader responsibilities or specialize in areas like:

  • Salesforce Cloud Integration Architect
  • Master Data Management Architect (Salesforce Focus)
  • Salesforce Analytics Architect
  • Salesforce Data Governance Lead
  • High demand and competitive salaries in the Salesforce ecosystem.
  • Opportunity to work on complex and impactful data-driven projects.
  • Play a critical role in ensuring the success of Salesforce implementations.
  • Continuously learn and stay updated with evolving Salesforce technologies.
  • Contribute to a data-driven culture within organizations.

Salaries vary depending on experience, location, and industry. According to various sources, the average base salary for Salesforce Data Architects in the US can range from $100,000 to $150,000 annually.

  • Salesforce Certified Data Architect (CDAD): Validates expertise in designing and implementing data architectures within Salesforce.
  • Other Salesforce Certifications: Administrator, Advanced Administrator, Platform App Builder can be beneficial along with the CDAD.
  • Balancing data integrity with user needs and business requirements.
  • Designing a scalable data model for future growth and evolving needs.
  • Ensuring data quality and consistency across various data sources.
  • Keeping up with the pace of innovation in the Salesforce platform and related technologies.
  • Managing complex data integrations with external systems.
  • Start with clear business requirements and understand user needs.
  • Normalize data to minimize redundancy and improve data integrity.
  • Leverage Salesforce object relationships effectively.
  • Define data governance standards for data ownership and access control.
  • Design for scalability to accommodate future data growth.
  • Implement data validation rules and data cleansing processes.
  • Leverage data quality tools for data profiling and anomaly detection.
  • Establish data governance processes for data ownership and stewardship.
  • Monitor data quality metrics and identify areas for improvement.
  • Encourage a data-driven culture within the organization.
  • Salesforce Data Loader and tools like Workbench
  • Data integration platforms (e.g., MuleSoft Anypoint, Informatica)
  • Data quality tools (e.g., Informatica Data Quality, Trifacta Wrangler)
  • Data visualization tools (e.g., Tableau, Salesforce Einstein Analytics)
  • Version control systems (e.g., Git)
  • Utilize Salesforce APIs and integration tools for data exchange.
  • Configure data mappings and transformations between Salesforce and external systems.
  • Ensure data security and compliance throughout the integration process.
  • Monitor and maintain the health of data integrations.

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